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3D Echo-Based Patient-Specific Computational Left Ventricle Models to Quantify Material Properties and Stress/Strain
Rui Fan1, Dalin Tang2, Jing Yao3
1School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China.
Abstract:
Identifying ventricle material properties and its infarct area after heart attack noninvasively is of great important in clinical applications. An echo-based computational modeling approach was proposed to investigate left ventricle (LV) mechanical properties and stress conditions using patient-specific data. Echo data was acquired from one healthy volunteer (male, age: 58) and a male patient (age: 60) who had an acute inferior myocardial infarction one week before echo image acquisition. Standard echocardiograms were obtained using an ultrasound machine (E9, GE Mechanical Systems, Milwaukee, Wisconsin) with a 3V probe and data were segmented for model construction. Finite element models were constructed to obtain ventricle stress and strain conditions. A pre-shrink process was applied so that the model ventricle geometries under end-of-systole pressure matched in vivo data. Our results indicated that the modeling approach has the potential to be used to determine ventricle material properties. The equivalent Young's modulus value from the healthy LV (LV1) was about 30% softer than that of the infarct LV (LV2) at end of diastole, but was about 100% stiffer than that of LV2 at end of systole. This can be explained as LV1 has more active contraction reflected by stiffness variations. Using averaged values, at end-systole, longitudinal curvature from LV2 was 164% higher than that from LV1. LV stress from LV2 was 82% higher than that from LV1. At end-diastole, L-curvature from LV2 was still 132% higher than that from LV1, while LV stress from LV2 was only 9% higher than that from LV1. Longitudinal curvature and stress showed the largest differences between the two ventricles, with the LV with infarct having higher longitudinal curvature and stress values. Large scale studies are needed to further confirm our findings.
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